Allan Vaccarizi This workflow corresponds to n8n.io template #8452 — we link there as the canonical source.
This workflow follows the Chainllm → Anthropic Chat recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"nodes": [
{
"id": "2329283c-ce3a-4412-ac45-573850ce65e7",
"name": "Sticky Note13",
"type": "n8n-nodes-base.stickyNote",
"position": [
-3600,
-736
],
"parameters": {
"width": 816,
"height": 336,
"content": "## Need more advanced automation solutions? Contact us for custom enterprise workflows!\n\n# Growth-AI.fr\n\n## https://www.linkedin.com/in/allanvaccarizi/\n## https://www.linkedin.com/in/hugo-marinier-%F0%9F%A7%B2-6537b633/"
},
"typeVersion": 1
},
{
"id": "81f896e8-b323-4acd-bdd8-d2e44d104eb8",
"name": "Sticky Note16",
"type": "n8n-nodes-base.stickyNote",
"position": [
-2752,
-768
],
"parameters": {
"width": 1024,
"height": 400,
"content": ""
},
"typeVersion": 1
},
{
"id": "581b68b8-ac61-4dd0-ac95-ba591a0f7f85",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-4080,
-304
],
"parameters": {
"width": 480,
"height": 944,
"content": "## AI monitoring \n\n### How it works\n\n1. A schedule trigger fires and fetches a list of watch topics from a data table, then loops over each topic.\n2. For each topic, the workflow searches Google News via SerpAPI, extracts the article URLs, and scrapes the full article content using Firecrawl.\n3. The scraped markdown is cleaned and passed to an Anthropic Claude LLM chain, which writes a structured news digest entry for that topic.\n4. Once all topics are processed, the compiled digests are aggregated and split into Discord-safe message chunks, while an intro message is sent immediately.\n5. Each digest chunk is sent to Discord in a loop, and a conclusion message is sent at the end to close the broadcast.\n\n### Setup steps\n\n- - [ ] Configure the **Schedule Trigger** with your desired run frequency (e.g., daily, weekly).\n- - [ ] Set up the **Get row(s)** node with credentials for your data table source (e.g., NocoDB, Airtable) and ensure it contains the list of watch topics.\n- - [ ] Add your **SerpAPI** API key to the Search GNews node for Google News searches.\n- - [ ] Add your **Firecrawl** API key to the Scrape article node for web scraping.\n- - [ ] Configure **Anthropic** credentials in the Anthropic Chat Model sub-node for the AI digest writing step.\n- - [ ] Set up the **Discord** nodes (Intro, Veille, Conclusion) with a Discord bot token and the correct channel ID.\n\n### Customization\n\nYou can adjust the AI prompt in 'R\u00e9daction veille' to change the tone or format of the digest. The 'D\u00e9coupage message discord' code node controls the Discord message chunk size \u2014 modify it if you hit Discord's 2000-character limit. You can also change the search query logic in 'Search GNews' to filter by language, region, or date range."
},
"typeVersion": 1
},
{
"id": "e3280242-6dcd-4f32-862f-2a72af245942",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-3520,
176
],
"parameters": {
"color": 7,
"width": 608,
"height": 304,
"content": "## Schedule and fetch topics\n\nTriggers the workflow on a schedule, fetches the list of watch topics from a data table, and feeds them into the processing loop."
},
"typeVersion": 1
},
{
"id": "9b7da681-f7ca-403a-bee3-cbdffc1f069b",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-2768,
144
],
"parameters": {
"color": 7,
"width": 400,
"height": 320,
"content": "## Search news and extract URLs\n\nFor each topic, searches Google News via SerpAPI and extracts only the relevant article URLs with a code node."
},
"typeVersion": 1
},
{
"id": "0f359031-01f8-425b-9ae1-3f2d68aa1320",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
-2272,
176
],
"parameters": {
"color": 7,
"width": 816,
"height": 464,
"content": "## Scrape, clean, and summarise\n\nScrapes the full article content via Firecrawl, cleans the raw markdown for AI consumption, then uses an Anthropic LLM chain to write a structured digest entry for the topic."
},
"typeVersion": 1
},
{
"id": "a714917d-55be-48dd-a7ce-dbd17004b7eb",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
-2832,
-272
],
"parameters": {
"color": 7,
"width": 896,
"height": 384,
"content": "## Aggregate and prepare Discord messages\n\nAggregates all topic digests into one dataset, sends an intro message to Discord, and splits the full digest into Discord-safe chunks ready for sequential sending."
},
"typeVersion": 1
},
{
"id": "6961f89e-69fd-436f-bd13-c8a5d1c678c4",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1904,
-304
],
"parameters": {
"color": 7,
"width": 624,
"height": 448,
"content": "## Send digest to Discord\n\nLoops over each message chunk and sends it to Discord, then sends a final conclusion message to close the broadcast."
},
"typeVersion": 1
},
{
"id": "d9c479e9-0ace-4ca5-a3bc-ff72bd64a290",
"name": "Claude Sonnet 4.6",
"type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
"position": [
-1760,
480
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "claude-sonnet-4-6",
"cachedResultName": "Claude Sonnet 4.6"
},
"options": {
"maxTokensToSample": 20000
}
},
"credentials": {
"anthropicApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "ff784c86-27fb-488a-b2ec-828a47c1985d",
"name": "Every Monday at 9am",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
-3472,
304
],
"parameters": {
"rule": {
"interval": [
{
"field": "cronExpression",
"expression": "0 9 * * 1"
}
]
}
},
"typeVersion": 1.2
},
{
"id": "389a8687-0fc0-4339-8eed-a114e1e5a3ca",
"name": "Loop Over Watch Topics",
"type": "n8n-nodes-base.splitInBatches",
"position": [
-3056,
304
],
"parameters": {
"options": {}
},
"typeVersion": 3
},
{
"id": "3328eb5e-be5a-4dae-882b-24b420aa6229",
"name": "Search Google News via SerpAPI",
"type": "n8n-nodes-serpapi.serpApi",
"position": [
-2720,
304
],
"parameters": {
"q": "={{ $json.Query }}",
"operation": "google_news",
"requestOptions": {},
"additionalFields": {}
},
"credentials": {
"serpApi": {
"name": "<your credential>"
}
},
"retryOnFail": true,
"typeVersion": 1
},
{
"id": "eb42701a-7e71-474c-bb9c-fc26244c8802",
"name": "Draft Watch Summary with AI",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"maxTries": 5,
"position": [
-1760,
304
],
"parameters": {
"text": "=Source 1\nURL : {{ $('Clean Markdown for AI').all()[0].json.link }}\nDate : {{ $('Clean Markdown for AI').all()[0].json.date }}\nContenu de l'article : {{ $('Clean Markdown for AI').all()[0].json.markdown_clean }}\n\nSource 2\nURL : {{ $('Clean Markdown for AI').all()[1].json.link }}\nDate : {{ $('Clean Markdown for AI').all()[1].json.date }}\nContenu de l'article : {{ $('Clean Markdown for AI').all()[1].json.markdown_clean }}\n\nSource 3\nURL : {{ $('Clean Markdown for AI').all()[2].json.link }}\nDate : {{ $('Clean Markdown for AI').all()[2].json.date }}\nContenu de l'article : {{ $('Clean Markdown for AI').all()[2].json.markdown_clean }}",
"batching": {},
"messages": {
"messageValues": [
{
"message": "=Voil\u00e0 le contenu de 3 article sur le th\u00e8me \"{{ $('Loop Over Watch Topics').first().json.Query }}\".\n\n\n# Mission\nAnalysez les articles fournis et produisez une synth\u00e8se structur\u00e9e.\n\n# Format de sortie requis\n\nUne fois au d\u00e9but : Veille **{{ $('Loop Over Watch Topics').first().json.Query }}**\n\nPuis pour chaque article, suivez exactement cette structure :\n\n```\n# Article [Titre]\n\n**M\u00e9dia :** [Nom du m\u00e9dia]\n**Date :** [Date de publication] \n**Lien :** [URL]\n**R\u00e9sum\u00e9 :** [2-3 phrases sur le contenu principal]\n\n---\n```\n\n## Consignes\n- Respecter l'ordre : M\u00e9dia \u2192 Date \u2192 Lien \u2192 R\u00e9sum\u00e9\n- Num\u00e9roter les articles dans l'ordre d'apparition\n- R\u00e9sum\u00e9 maximum 3 phrases\n- Si une info manque, indiquer \"Non disponible\"\n\nSi il manque les informations d'un article ignore le et fait un rendu cons\u00e9quent au nombre d'article que tu a pu traiter).\n\nTraitez maintenant le document fourni et donnez un rendu en fran\u00e7ais."
}
]
},
"promptType": "define"
},
"executeOnce": true,
"retryOnFail": true,
"typeVersion": 1.7
},
{
"id": "40c57253-ce87-49af-94ba-d2f64da31d73",
"name": "Aggregate All Summaries",
"type": "n8n-nodes-base.aggregate",
"position": [
-2784,
-64
],
"parameters": {
"include": "specifiedFields",
"options": {},
"aggregate": "aggregateAllItemData",
"fieldsToInclude": "text"
},
"typeVersion": 1
},
{
"id": "a1e9c64e-6168-4021-b93b-e16b567f27e4",
"name": "Split Text for Discord",
"type": "n8n-nodes-base.code",
"position": [
-2448,
-80
],
"parameters": {
"jsCode": "// Code pour node n8n - Division de texte pour Discord\n// Limite Discord : 2000 caract\u00e8res par message\n\nconst DISCORD_CHAR_LIMIT = 2000;\nconst SAFETY_MARGIN = 50; // Marge de s\u00e9curit\u00e9 pour \u00e9viter les d\u00e9passements\nconst EFFECTIVE_LIMIT = DISCORD_CHAR_LIMIT - SAFETY_MARGIN;\n\nfunction splitTextForDiscord(text) {\n // Si le texte est plus court que la limite, on le retourne tel quel\n if (text.length <= EFFECTIVE_LIMIT) {\n return [text];\n }\n\n const messages = [];\n let currentMessage = '';\n \n // Diviser le texte en paragraphes d'abord (s\u00e9par\u00e9s par \\n\\n ou ----)\n const sections = text.split(/(?:\\n\\n|----)/);\n \n for (let i = 0; i < sections.length; i++) {\n let section = sections[i].trim();\n \n // Si une section compl\u00e8te d\u00e9passe la limite, la diviser par phrases\n if (section.length > EFFECTIVE_LIMIT) {\n const sentences = section.split(/(?<=[.!?:])\\s+/);\n \n for (const sentence of sentences) {\n // Si une phrase seule d\u00e9passe la limite, la couper brutalement\n if (sentence.length > EFFECTIVE_LIMIT) {\n const chunks = splitByLength(sentence, EFFECTIVE_LIMIT);\n for (const chunk of chunks) {\n if (currentMessage.length + chunk.length + 1 > EFFECTIVE_LIMIT) {\n if (currentMessage.trim()) {\n messages.push(currentMessage.trim());\n }\n currentMessage = chunk;\n } else {\n currentMessage += (currentMessage ? ' ' : '') + chunk;\n }\n }\n } else {\n // Ajouter la phrase si elle rentre dans le message actuel\n if (currentMessage.length + sentence.length + 1 <= EFFECTIVE_LIMIT) {\n currentMessage += (currentMessage ? ' ' : '') + sentence;\n } else {\n // Sauvegarder le message actuel et commencer un nouveau\n if (currentMessage.trim()) {\n messages.push(currentMessage.trim());\n }\n currentMessage = sentence;\n }\n }\n }\n } else {\n // La section rentre dans la limite, v\u00e9rifier si elle rentre dans le message actuel\n if (currentMessage.length + section.length + 2 <= EFFECTIVE_LIMIT) {\n currentMessage += (currentMessage ? '\\n\\n' : '') + section;\n } else {\n // Sauvegarder le message actuel et commencer un nouveau\n if (currentMessage.trim()) {\n messages.push(currentMessage.trim());\n }\n currentMessage = section;\n }\n }\n }\n \n // Ajouter le dernier message s'il existe\n if (currentMessage.trim()) {\n messages.push(currentMessage.trim());\n }\n \n return messages.length > 0 ? messages : [text];\n}\n\nfunction splitByLength(text, maxLength) {\n const chunks = [];\n for (let i = 0; i < text.length; i += maxLength) {\n chunks.push(text.slice(i, i + maxLength));\n }\n return chunks;\n}\n\n// Code principal pour n8n\nconst inputData = $input.all();\nconst outputItems = [];\n\nfor (let i = 0; i < inputData.length; i++) {\n const item = inputData[i];\n \n // Extraire le texte \u00e0 diviser (adaptez selon votre structure de donn\u00e9es)\n // Exemple : si votre texte est dans item.json.content\n let textToSplit = '';\n \n // Si c'est un tableau comme dans votre exemple\n if (item.json.data && Array.isArray(item.json.data)) {\n textToSplit = item.json.data.map(dataItem => dataItem.text || '').join('\\n\\n---\\n\\n');\n } \n // Si c'est directement du texte\n else if (item.json.text) {\n textToSplit = item.json.text;\n }\n // Si c'est dans un autre champ\n else if (item.json.content) {\n textToSplit = item.json.content;\n }\n // Fallback : convertir tout l'objet en texte\n else {\n textToSplit = JSON.stringify(item.json, null, 2);\n }\n \n // Diviser le texte\n const messages = splitTextForDiscord(textToSplit);\n \n // Cr\u00e9er un item de sortie pour chaque message\n messages.forEach((message, index) => {\n outputItems.push({\n json: {\n message: message,\n messageIndex: index + 1,\n totalMessages: messages.length,\n characterCount: message.length,\n originalItemIndex: i\n }\n });\n });\n}\n\nreturn outputItems;"
},
"typeVersion": 2
},
{
"id": "168294e9-07b5-4d23-b3f7-bcc8c92aebee",
"name": "Send Intro to Discord",
"type": "n8n-nodes-base.discord",
"position": [
-2096,
-176
],
"parameters": {
"content": "Hello everyone ! \n\nHere is your weekly dose of news !",
"guildId": {
"__rl": true,
"mode": "list",
"value": "919951151888236595",
"cachedResultUrl": "https://discord.com/channels/919951151888236595",
"cachedResultName": "Institut du r\u00e9f\u00e9rencement"
},
"options": {},
"resource": "message",
"channelId": {
"__rl": true,
"mode": "list",
"value": "1334455789284364309",
"cachedResultUrl": "https://discord.com/channels/919951151888236595/1334455789284364309",
"cachedResultName": "\ud83d\udcdd-veille-\ud83d\udcdd"
}
},
"credentials": {
"discordBotApi": {
"name": "<your credential>"
}
},
"typeVersion": 2
},
{
"id": "96815712-69d1-406b-a8cc-6604aadf47a4",
"name": "Send Watch Chunk to Discord",
"type": "n8n-nodes-base.discord",
"position": [
-1632,
-32
],
"parameters": {
"content": "={{ $json.message }}",
"guildId": {
"__rl": true,
"mode": "list",
"value": "919951151888236595",
"cachedResultUrl": "https://discord.com/channels/919951151888236595",
"cachedResultName": "Institut du r\u00e9f\u00e9rencement"
},
"options": {
"flags": [
"SUPPRESS_EMBEDS"
]
},
"resource": "message",
"channelId": {
"__rl": true,
"mode": "list",
"value": "1334455789284364309",
"cachedResultUrl": "https://discord.com/channels/919951151888236595/1334455789284364309",
"cachedResultName": "\ud83d\udcdd-veille-\ud83d\udcdd"
}
},
"credentials": {
"discordBotApi": {
"name": "<your credential>"
}
},
"typeVersion": 2
},
{
"id": "1e74b9d2-5c43-4186-91aa-ca3a7a168b8e",
"name": "Send Conclusion to Discord",
"type": "n8n-nodes-base.discord",
"position": [
-1424,
-176
],
"parameters": {
"content": "ET VOIL\u00c0 MINIONS ORGANIQUES ! Claptrap a termin\u00e9 sa mission \u00c9PIQUE - \u00e0 la semaine prochaine pour encore plus d'excellence robotique ! Bip boop \ud83e\udd16\u2728",
"guildId": {
"__rl": true,
"mode": "list",
"value": "919951151888236595",
"cachedResultUrl": "https://discord.com/channels/919951151888236595",
"cachedResultName": "Institut du r\u00e9f\u00e9rencement"
},
"options": {},
"resource": "message",
"channelId": {
"__rl": true,
"mode": "list",
"value": "1334455789284364309",
"cachedResultUrl": "https://discord.com/channels/919951151888236595/1334455789284364309",
"cachedResultName": "\ud83d\udcdd-veille-\ud83d\udcdd"
}
},
"credentials": {
"discordBotApi": {
"name": "<your credential>"
}
},
"executeOnce": true,
"typeVersion": 2
},
{
"id": "ad55964a-3a23-4bf8-ae79-0b4da47ad3b8",
"name": "Loop Over Discord Chunks",
"type": "n8n-nodes-base.splitInBatches",
"position": [
-1856,
-96
],
"parameters": {
"options": {}
},
"typeVersion": 3
},
{
"id": "a183fb42-04e4-4c82-8a85-5dc61d532d44",
"name": "Extract Article URLs",
"type": "n8n-nodes-base.code",
"position": [
-2512,
304
],
"parameters": {
"jsCode": "const inputData = $input.all()[0].json;\nconst newsResults = inputData.news_results || [];\n\nconst sortedResults = newsResults.sort((a, b) => a.position - b.position);\nconst top3 = sortedResults.slice(0, 3);\n\nreturn top3.map(item => ({\n json: {\n link: item.link || null,\n date: item.date || null\n }\n}));"
},
"typeVersion": 2
},
{
"id": "0e1f5e35-fb2c-4cc3-9597-ac2ec28d543a",
"name": "Load Watch Topics from Table",
"type": "n8n-nodes-base.dataTable",
"position": [
-3264,
304
],
"parameters": {
"operation": "get",
"returnAll": true,
"dataTableId": {
"__rl": true,
"mode": "list",
"value": "CcsQaNMfQNPMQsOR",
"cachedResultUrl": "/projects/oTpNUA7ZOCuhiQA0/datatables/CcsQaNMfQNPMQsOR",
"cachedResultName": "Query Veille"
}
},
"typeVersion": 1
},
{
"id": "b524120a-91fd-45d8-9b2e-d4b94113b251",
"name": "Scrape Article Content",
"type": "@mendable/n8n-nodes-firecrawl.firecrawl",
"onError": "continueRegularOutput",
"maxTries": 5,
"position": [
-2224,
304
],
"parameters": {
"url": "={{ $json.link }}",
"operation": "scrape",
"requestOptions": {}
},
"credentials": {
"firecrawlApi": {
"name": "<your credential>"
}
},
"retryOnFail": true,
"typeVersion": 1,
"alwaysOutputData": false
},
{
"id": "235ed5ec-be74-4b7a-8ae3-15ff22b6506b",
"name": "Clean Markdown for AI",
"type": "n8n-nodes-base.code",
"onError": "continueRegularOutput",
"position": [
-2016,
304
],
"parameters": {
"jsCode": "const items = $input.all();\n\nfunction cleanMarkdown(text) {\n if (!text) return '';\n \n let cleaned = text;\n \n cleaned = cleaned.replace(/passer au contenu principal/gi, '');\n cleaned = cleaned.replace(/aller au contenu/gi, '');\n cleaned = cleaned.replace(/\\[([^\\]]+)\\]\\([^\\)]+\\)/g, '$1');\n cleaned = cleaned.replace(/\\[([^\\]]+)\\]/g, '$1');\n cleaned = cleaned.replace(/https?:\\/\\/[^\\s)]+/g, '');\n cleaned = cleaned.replace(/www\\.[^\\s)]+/g, '');\n cleaned = cleaned.replace(/\\([^)]*(?:http|www)[^)]*\\)/g, '');\n cleaned = cleaned.replace(/ +/g, ' ');\n cleaned = cleaned.replace(/\\n{3,}/g, '\\n\\n');\n cleaned = cleaned.split('\\n').map(line => line.trim()).join('\\n');\n cleaned = cleaned.trim();\n \n return cleaned;\n}\n\nconst links = $('Extract Article URLs').all();\n\nreturn items.map((item, index) => ({\n json: {\n link: links[index]?.json.link || null,\n date: links[index]?.json.date || null,\n markdown_clean: cleanMarkdown(item.json.data.markdown)\n }\n}));"
},
"typeVersion": 2,
"alwaysOutputData": false
}
],
"connections": {
"Claude Sonnet 4.6": {
"ai_languageModel": [
[
{
"node": "Draft Watch Summary with AI",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Every Monday at 9am": {
"main": [
[
{
"node": "Load Watch Topics from Table",
"type": "main",
"index": 0
}
]
]
},
"Extract Article URLs": {
"main": [
[
{
"node": "Scrape Article Content",
"type": "main",
"index": 0
}
]
]
},
"Clean Markdown for AI": {
"main": [
[
{
"node": "Draft Watch Summary with AI",
"type": "main",
"index": 0
}
]
]
},
"Loop Over Watch Topics": {
"main": [
[
{
"node": "Aggregate All Summaries",
"type": "main",
"index": 0
}
],
[
{
"node": "Search Google News via SerpAPI",
"type": "main",
"index": 0
}
]
]
},
"Scrape Article Content": {
"main": [
[
{
"node": "Clean Markdown for AI",
"type": "main",
"index": 0
}
]
]
},
"Split Text for Discord": {
"main": [
[
{
"node": "Loop Over Discord Chunks",
"type": "main",
"index": 0
}
]
]
},
"Aggregate All Summaries": {
"main": [
[
{
"node": "Split Text for Discord",
"type": "main",
"index": 0
},
{
"node": "Send Intro to Discord",
"type": "main",
"index": 0
}
]
]
},
"Loop Over Discord Chunks": {
"main": [
[
{
"node": "Send Conclusion to Discord",
"type": "main",
"index": 0
}
],
[
{
"node": "Send Watch Chunk to Discord",
"type": "main",
"index": 0
}
]
]
},
"Draft Watch Summary with AI": {
"main": [
[
{
"node": "Loop Over Watch Topics",
"type": "main",
"index": 0
}
]
]
},
"Send Watch Chunk to Discord": {
"main": [
[
{
"node": "Loop Over Discord Chunks",
"type": "main",
"index": 0
}
]
]
},
"Load Watch Topics from Table": {
"main": [
[
{
"node": "Loop Over Watch Topics",
"type": "main",
"index": 0
}
]
]
},
"Search Google News via SerpAPI": {
"main": [
[
{
"node": "Extract Article URLs",
"type": "main",
"index": 0
}
]
]
}
}
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
anthropicApidiscordBotApifirecrawlApiserpApi
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About this workflow
📺 Full walkthrough video: https://youtu.be/QHvfykuSbF8
Source: https://n8n.io/workflows/8452/ — original creator credit. Request a take-down →
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📺 Full walkthrough video: https://youtu.be/dXz5OTbm4c8
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